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NEW QUESTION: 1
An application has two entities, Department and Employee, and there is a one-to-many relationship between them. The application has the following query:
SELECT d
FROM Department d LEFT JOIN FETCH d. employees
WHERE d.name = : name
After receiving the results of the query, the application accesses the returned department's Employee entities stored in the Department.employees collection-valued attribute.
All caching has been turned off in the application.
Which statement is true?
A. The database will be accessed once during the query execution phase, and once for each Employee entity in Department - employees.
B. The database will be accessed once during the query execution phase ONLY.
C. The database will be accessed once during the query execution phase, and once when the department.employees collection-valued attribute is used.
D. The database will be accessed once during the query execution phase, once when the Department.
Employees collection-valued attribute is used, and once for each employee entity in the Department.employees.
Answer: B
Explanation:
Explanation/Reference:
An important use case for LEFT JOIN is in enabling the prefetching of related data items as a side effect of a query. This is accomplished by specifying the LEFT JOIN as a FETCH JOIN.
10.2.3.5.3. JPQL Fetch Joins
A FETCH JOIN enables the fetching of an association as a side effect of the execution of a query. A FETCH JOIN is specified over an entity and its related entities. The syntax for a fetch join is fetch_join ::= [ LEFT [OUTER] | INNER ] JOIN FETCH join_association_path_expression The association referenced by the right side of the FETCH JOIN clause must be an association that belongs to an entity that is returned as a result of the query. It is not permitted to specify an identification variable for the entities referenced by the right side of the FETCH JOIN clause, and hence references to the implicitly fetched entities cannot appear elsewhere in the query. The following query returns a set of magazines. As a side effect, the associated articles for those magazines are also retrieved, even though they are not part of the explicit query result. The persistent fields or properties of the articles that are eagerly fetched are fully initialized. The initialization of the relationship properties of the articles that are retrieved is determined by the metadata for the Article entity class.
SELECT mag FROM Magazine mag LEFT JOIN FETCH mag.articles WHERE mag.id = 1 A fetch join has the same join semantics as the corresponding inner or outer join, except that the related objects specified on the right-hand side of the join operation are not returned in the query result or otherwise referenced in the query. Hence, for example, if magazine id 1 has five articles, the above query returns five references to the magazine 1 entity.
Reference: Oracle Fusion Middleware Kodo Developers Guide for JPA/JDO

NEW QUESTION: 2

A. Azure Machine Learning
B. Azure Stream Analytics
C. Azure Data Lake Analytics
D. Azure HDInsight Storm clusters
Answer: B
Explanation:
Explanation
Azure Stream Analytics is a fully managed event-processing engine that lets you set up real-time analytic computations on streaming data.
Scalability
Stream Analytics can handle up to 1 GB of incoming data per second. Integration with Azure Event Hubs and Azure IoT Hub allows jobs to ingest millions of events per second coming from connected devices, clickstreams, and log files, to name a few. Using the partition feature of event hubs, you can partition computations into logical steps, each with the ability to be further partitioned to increase scalability.
Topic 1, RelecloudGeneral Overview
Relecloud is a social media company that processes hundreds of millions of social media posts per day and sells advertisements to several hundred companies.
Relecloud has a Microsoft SQL Server database named DB1 that stores information about the advertisers.
DB1 is hosted on a Microsoft Azure virtual machine.
Physical locations
Relecloud has two main offices. The offices we located in San Francisco and New York City.
The offices connected to each other by using a site-to-site VPN. Each office connects directly to the Internet.
Business model
Relecloud modifies the pricing of its advertisements based on trending topics. Topics are considered to be trending if they generate many mentions in a specific country during a 15-minute time frame. The highest trending topics generate the highest advertising revenue.
CTO statement
Relecloud wants to deliver reports lo the advertisers by using Microsoft Power BI. The reports will provide real-time data on trending topics, current advertising rates, and advertising costs for a given month.
Relecloud will analyze the trending topics data, and then store the data in a new data warehouse for ad-hoc analysis. The data warehouse is expected to grow at a rate of 1 GB per hour or 8.7 terabytes (TB) per year. The data will be retained for five years for the purpose of long term trending.
Requirements
Business goals
Management at Relecloud must be able to view which topics are trending to adjust advertising rates in near real-time.
Planned changes
Relecloud plans to implement a new streaming analytics platform that will report on trending topics.
Relecloud plans to implement a data warehouse named DB2.
General technical requirements
Relecloud identifies the following technical requirements:
* Social media data must be analyzed to identify trending topics in real time.
* The use of Infrastructure as a Service (IaaS) platforms must minimized, whenever possible.
* The real-time solution used to analyze the social media data must support selling up and down without service interruption.
Technical requirements for advertisers
Relecloud identifies the following technical requirements for the advertisers
* The advertisers must be able to see only their own data in the Power BI reports.
* The advertisers must authenticate to Power BI by using Azure Active Directory (Azure AD) credentials.
* The advertisers must be able to leverage existing Transact-SQL language knowledge when developing the real-time streaming solution.
* Members of the internal advertising sales team at Relecloud must be able to see only the sales data of the advertisers to which they are assigned.
* The Internal Relecloud advertising sales team must be prevented from inserting, updating, and deleting rows for the advertisers to which they are not assigned.
* The internal Relecloud advertising sales team must be able to use a text file to update the list of advertisers, and then to upload the file to Azure Blob storage.
DB1 requirements
Relecloud identifies the following requirements for DB1:
* Data generated by the streaming analytics platform must be stored in DB1.
* The user names of the advertisers must be mapped to CustomerID in a table named Table2.
* The advertisers in DB1 must be stored in a table named Table1 and must be refreshed nightly.
* The user names of the employees at Relecloud must be mapped to EmployeeID in a table named Table3.
DB2 requirements
Relecloud identifies the following requirements for DB2:
* DB2 must have minimal storage costs.
* DB2 must run load processes in parallel.
* DB2 must support massive parallel processing.
* DB2 must be able to store more than 40 TB of data.
* DB2 must support scaling up and down, as required.
* Data from DB1 must be archived in DB2 for long-term storage.
* All of the reports that are executed from DB2 must use aggregation.
* Users must be able to pause DB2 when the data warehouse is not in use.
* Users must be able to view previous versions of the data in DB2 by using aggregates.
ETL requirements
Relecloud identifies the following requirements for extract, transformation, and load (ETL):
* Data movement between DB1 and DB2 must occur each hour.
* An email alert must be generated when a failure of any type occurs during ETL processing.
rls_table1
You execute the following code for a table named rls_table1.

dbo.table1
You use the following code to create Table1.

Streaming data
The following is a sample of the Streaming data.

NEW QUESTION: 3
Which of the following inherits from Zend_Log_Writer_Abstract and is responsible for saving data to storage?
A. Formatter
B. Log
C. Writer
D. Filter
Answer: C

NEW QUESTION: 4
애플리케이션이 이동 된 후 App1에 대한 백업 솔루션을 구현해야 합니다.
무엇을 먼저 만들어야 합니까?
A. Azure 백업 서버
B. 복구 서비스 저장소
C. 복구 계획
D. 백업 정책
Answer: B
Explanation:
설명
Recovery Services 자격 증명 모음은 Azure VM과 같은 보호된 각 리소스에 대한 백업 데이터를 저장하는 논리적 컨테이너입니다. 보호된 리소스에 대한 백업 작업이 실행되면 Recovery Services 볼트 내에 복구 지점이 생성됩니다.
대본:
각각 5 개의 가상 머신이있는 3 개의 애플리케이션 계층이 있습니다.
App1의 모든 가상 컴퓨터를 Azure로 이동합니다.
App1의 모든 가상 머신이 백업으로 보호되는지 확인하십시오.
참조 : https://docs.microsoft.com/en-us/azure/backup/quick-backup-vm-portal